Surveillance of human subjects is how data-intensive companies obtain much of their data, yet surveillance increasingly meets with social and regulatory resistance. Data-intensive companies are thus seeking other ways to meet their data needs. This article explores one of these: the creation of synthetic data, or data produced artificially as an alternative to real-world data. I show that capital is already heavily invested in synthetic data. I argue that its appeal goes beyond circumventing surveillance to accord with a structural tendency within capitalism toward the autonomization of the circuit of capital. By severing data from human subjectivity, synthetic data contributes to the automation of the production of automation technologies like machine learning. A shift from surveillance to synthesis, I argue, has epistemological, ontological, and political economic consequences for a society increasingly structured around data-intensive capital.

对人类受试者的监视是数据密集型公司获取大部分数据的方式，但监视越来越多地遇到社会和监管阻力。因此，数据密集型公司正在寻求其他方式来满足其数据需求。本文探讨其中之一：合成数据的创建，或人工生成的数据，以替代现实世界的数据。我表明，资本已经大量投资于合成数据。我认为，它的吸引力超出了规避监督的范围，以符合资本主义内部朝着资本循环自主化的结构趋势。通过从人类主观性中分离数据，合成数据有助于机器学习等自动化技术的生产自动化。我认为，从监视到综合的转变具有认识论、本体论、